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Build a Python chat app using Ollama-py and Streamlit. Learn to implement key features like user input, message history, model selection, and streaming responses.
Learn to build your first LangChain, exploring Runnable, message formats, ChatModel, templates, and combining components for complex LLM-powered logic in just 14 minutes.
Explore Meta's Llama3 models: architecture, training, benchmarks, and real-world performance. Discover how this open-source AI compares to competitors and its potential impact on the field.
Build a RAG system with Python and Ollama: parse documents, create embeddings, implement relevance scoring, and enable LLM interaction with your own datasets.
Enhance your self-hosted Ollama models with Ollama Web UI, featuring a sleek interface, chat history, voice input, and user management. Learn to access it on your phone using Ngrok for on-the-go AI interactions.
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